In this paper, we study the problem of wideband spectrum sensing for cognitive radio
networks by partitioning it into four fundamental elements: system modeling, performance …

It is recently shown that algorithms derived from random matrix theory (RMT) can provide
superior performance for spectrum sensing, which corresponds to the task of detecting the …

Cognitive Radio (CR) networks presents a paradigm shift aiming to alleviate the spectrum
scarcity problem exasperated by the increasing demand on this limited resource. It promotes …

Sampling theories lie at the heart of signal processing devices and communication systems.
To accommodate high operating rates while retaining low computational cost, efficient …

This paper presents a novel power spectral density estimation technique for band-limited,
wide-sense stationary signals from sub-Nyquist sampled data. The technique employs multi …

This paper introduces a multiband spectrum sensing technique that utilizes nonuniform
stratified sampling. Capitalising on the ability of the sampling scheme to suppress aliasing …

This paper introduces a novel method of spectrum sensing in communication systems that
utilizes nonuniform sampling in conjunction with a suitable spectral analysis tool. It is …

Examples of wideband spectrum sensing techniques for cognitive radio are provided. The
techniques permit undersampling (eg, sub-Nyquist sampling) the spectrum band, which …

This paper presents a method that deploys nonuniform sampling and appropriates to it a
processing algorithm to monitor the activity of a number of non-overlapping spectral bands …

This paper establishes a unified model for sub-Nyquist sampling and discusses different
aliasing patterns inherent in sub-Nyquist sampling. Several sub-Nyquist sampling schemes …